Data Engineer

Nederlander Producing Company of America•New York, NY

About The Position

We are seeking a Data Engineer to join our team. This role involves designing, building, and operating scalable data pipelines and infrastructure. You will be responsible for managing data architecture in Snowflake, developing transformation layers with dbt, and ensuring data quality and reliability. The position also involves automating processes, enabling downstream analytics, and supporting dynamic pricing models. This is an opportunity to lead data architecture strategy, build scalable infrastructure, and directly impact revenue through pricing optimization systems.

Requirements

Strong proficiency in SQL and advanced data modeling (dimensional + canonical)
Experience building and operating data pipelines using Python and modern data stack tools (Fivetran, dbt, HighTouch or similar)
Deep experience with Snowflake or similar cloud data warehouses
Experience working with CRM systems (Salesforce preferred)
Experience managing data infrastructure in AWS or similar cloud environments
Strong understanding of ETL/ELT design patterns, APIs, and distributed data systems

Nice To Haves

Reliable, scalable data pipelines with minimal manual intervention
Improved data quality and reduced duplication/errors
Faster reporting and improved data accessibility across teams
Successful deployment and iteration of pricing models supported by robust data systems

Responsibilities

Design, build, and operate scalable data pipelines across Salesforce, Snowflake, and external systems (ticketing, lottery, partners)
Leverage Fivetran and API-based ingestion frameworks to standardize and automate data ingestion from third-party platforms
Own API, webhook and file-based ingestion systems (SFTP, third-party feeds), ensuring reliability and observability
Manage AWS infrastructure supporting data ingestion, processing, and orchestration
Own Snowflake data architecture, including schema design, transformations, and data modeling
Develop and maintain transformation layers using dbt, including modular, testable, and well-documented models
Build canonical datasets and dimensional models supporting analytics, CRM, ticketing, and pricing
Optimize warehouse performance, cost, and scalability through clustering, partitioning, and query optimization
Manage schema evolution and deprecation of legacy data structures
Establish data quality frameworks using dbt tests, monitoring tools, and pipeline validation checks to detect and resolve inconsistencies, duplication, and missing data
Implement automated validation, monitoring, and alerting across pipelines
Own data hygiene standards across customer, order, and transaction datasets
Develop Python-based workflows to automate ingestion, transformation, and operational processes
Reduce manual workflows through system design, tooling, and pipeline reliability improvements
Leverage HighTouch to operationalize data by syncing curated datasets back into Salesforce and other business systems
Partner with third-party developers to maintain ticket lottery systems
Continuously improve pipeline performance, latency, and failure recovery
Build and maintain data pipelines supporting core reporting (sales, marketing performance, partner reporting)
Enable downstream analytics and BI through clean, accessible, and well-modeled datasets
Own the data infrastructure supporting dynamic pricing models
Design and maintain model-ready datasets across pricing, inventory, and demand signals using Snowflake and dbt
Partner with internal teams and external consultants to operationalize pricing models within Snowflake
Enable rapid iteration, backtesting, and deployment of pricing strategies